function d() {
    const SQRT3 = /*#__PURE__*/ Math.sqrt(3.0);
    const SQRT5 = /*#__PURE__*/ Math.sqrt(5.0);
    const F2 = 0.5 * (SQRT3 - 1.0);
    const G2 = (3.0 - SQRT3) / 6.0;
    const F3 = (/* unused pure expression or super */ null && (1.0 / 3.0));
    const G3 = (/* unused pure expression or super */ null && (1.0 / 6.0));
    const F4 = (SQRT5 - 1.0) / 4.0;
    const G4 = (5.0 - SQRT5) / 20.0;
    // I'm really not sure why this | 0 (basically a coercion to int)
    // is making this faster but I get ~5 million ops/sec more on the
    // benchmarks across the board or a ~10% speedup.
    const fastFloor = (x) => Math.floor(x) | 0;
    const grad2 = /*#__PURE__*/ new Float64Array([1, 1,
        -1, 1,
        1, -1,
        -1, -1,
        1, 0,
        -1, 0,
        1, 0,
        -1, 0,
        0, 1,
        0, -1,
        0, 1,
        0, -1]);
    // double seems to be faster than single or int's
    // probably because most operations are in double precision
    const grad3 = /*#__PURE__*/ new Float64Array([1, 1, 0,
        -1, 1, 0,
        1, -1, 0,
        -1, -1, 0,
        1, 0, 1,
        -1, 0, 1,
        1, 0, -1,
        -1, 0, -1,
        0, 1, 1,
        0, -1, 1,
        0, 1, -1,
        0, -1, -1]);
    // double is a bit quicker here as well
    const grad4 = /*#__PURE__*/ new Float64Array([0, 1, 1, 1, 0, 1, 1, -1, 0, 1, -1, 1, 0, 1, -1, -1,
        0, -1, 1, 1, 0, -1, 1, -1, 0, -1, -1, 1, 0, -1, -1, -1,
        1, 0, 1, 1, 1, 0, 1, -1, 1, 0, -1, 1, 1, 0, -1, -1,
        -1, 0, 1, 1, -1, 0, 1, -1, -1, 0, -1, 1, -1, 0, -1, -1,
        1, 1, 0, 1, 1, 1, 0, -1, 1, -1, 0, 1, 1, -1, 0, -1,
        -1, 1, 0, 1, -1, 1, 0, -1, -1, -1, 0, 1, -1, -1, 0, -1,
        1, 1, 1, 0, 1, 1, -1, 0, 1, -1, 1, 0, 1, -1, -1, 0,
        -1, 1, 1, 0, -1, 1, -1, 0, -1, -1, 1, 0, -1, -1, -1, 0]);
    /**
     * Creates a 2D noise function
     * @param random the random function that will be used to build the permutation table
     * @returns {NoiseFunction2D}
     */
    function createNoise2D(random = Math.random) {
        const perm = buildPermutationTable(random);
        // precalculating this yields a little ~3% performance improvement.
        const permGrad2x = new Float64Array(perm).map(v => grad2[(v % 12) * 2]);
        const permGrad2y = new Float64Array(perm).map(v => grad2[(v % 12) * 2 + 1]);
        return function noise2D(x, y) {
            // if(!isFinite(x) || !isFinite(y)) return 0;
            let n0 = 0; // Noise contributions from the three corners
            let n1 = 0;
            let n2 = 0;
            // Skew the input space to determine which simplex cell we're in
            const s = (x + y) * F2; // Hairy factor for 2D
            const i = fastFloor(x + s);
            const j = fastFloor(y + s);
            const t = (i + j) * G2;
            const X0 = i - t; // Unskew the cell origin back to (x,y) space
            const Y0 = j - t;
            const x0 = x - X0; // The x,y distances from the cell origin
            const y0 = y - Y0;
            // For the 2D case, the simplex shape is an equilateral triangle.
            // Determine which simplex we are in.
            let i1, j1; // Offsets for second (middle) corner of simplex in (i,j) coords
            if (x0 > y0) {
                i1 = 1;
                j1 = 0;
            } // lower triangle, XY order: (0,0)->(1,0)->(1,1)
            else {
                i1 = 0;
                j1 = 1;
            } // upper triangle, YX order: (0,0)->(0,1)->(1,1)
            // A step of (1,0) in (i,j) means a step of (1-c,-c) in (x,y), and
            // a step of (0,1) in (i,j) means a step of (-c,1-c) in (x,y), where
            // c = (3-sqrt(3))/6
            const x1 = x0 - i1 + G2; // Offsets for middle corner in (x,y) unskewed coords
            const y1 = y0 - j1 + G2;
            const x2 = x0 - 1.0 + 2.0 * G2; // Offsets for last corner in (x,y) unskewed coords
            const y2 = y0 - 1.0 + 2.0 * G2;
            // Work out the hashed gradient indices of the three simplex corners
            const ii = i & 255;
            const jj = j & 255;
            // Calculate the contribution from the three corners
            let t0 = 0.5 - x0 * x0 - y0 * y0;
            if (t0 >= 0) {
                const gi0 = ii + perm[jj];
                const g0x = permGrad2x[gi0];
                const g0y = permGrad2y[gi0];
                t0 *= t0;
                // n0 = t0 * t0 * (grad2[gi0] * x0 + grad2[gi0 + 1] * y0); // (x,y) of grad3 used for 2D gradient
                n0 = t0 * t0 * (g0x * x0 + g0y * y0);
            }
            let t1 = 0.5 - x1 * x1 - y1 * y1;
            if (t1 >= 0) {
                const gi1 = ii + i1 + perm[jj + j1];
                const g1x = permGrad2x[gi1];
                const g1y = permGrad2y[gi1];
                t1 *= t1;
                // n1 = t1 * t1 * (grad2[gi1] * x1 + grad2[gi1 + 1] * y1);
                n1 = t1 * t1 * (g1x * x1 + g1y * y1);
            }
            let t2 = 0.5 - x2 * x2 - y2 * y2;
            if (t2 >= 0) {
                const gi2 = ii + 1 + perm[jj + 1];
                const g2x = permGrad2x[gi2];
                const g2y = permGrad2y[gi2];
                t2 *= t2;
                // n2 = t2 * t2 * (grad2[gi2] * x2 + grad2[gi2 + 1] * y2);
                n2 = t2 * t2 * (g2x * x2 + g2y * y2);
            }
            // Add contributions from each corner to get the final noise value.
            // The result is scaled to return values in the interval [-1,1].
            return 70.0 * (n0 + n1 + n2);
        };
    }
    /**
     * Creates a 3D noise function
     * @param random the random function that will be used to build the permutation table
     * @returns {NoiseFunction3D}
     */
    function createNoise3D(random = Math.random) {
        const perm = buildPermutationTable(random);
        // precalculating these seems to yield a speedup of over 15%
        const permGrad3x = new Float64Array(perm).map(v => grad3[(v % 12) * 3]);
        const permGrad3y = new Float64Array(perm).map(v => grad3[(v % 12) * 3 + 1]);
        const permGrad3z = new Float64Array(perm).map(v => grad3[(v % 12) * 3 + 2]);
        return function noise3D(x, y, z) {
            let n0, n1, n2, n3; // Noise contributions from the four corners
            // Skew the input space to determine which simplex cell we're in
            const s = (x + y + z) * F3; // Very nice and simple skew factor for 3D
            const i = fastFloor(x + s);
            const j = fastFloor(y + s);
            const k = fastFloor(z + s);
            const t = (i + j + k) * G3;
            const X0 = i - t; // Unskew the cell origin back to (x,y,z) space
            const Y0 = j - t;
            const Z0 = k - t;
            const x0 = x - X0; // The x,y,z distances from the cell origin
            const y0 = y - Y0;
            const z0 = z - Z0;
            // For the 3D case, the simplex shape is a slightly irregular tetrahedron.
            // Determine which simplex we are in.
            let i1, j1, k1; // Offsets for second corner of simplex in (i,j,k) coords
            let i2, j2, k2; // Offsets for third corner of simplex in (i,j,k) coords
            if (x0 >= y0) {
                if (y0 >= z0) {
                    i1 = 1;
                    j1 = 0;
                    k1 = 0;
                    i2 = 1;
                    j2 = 1;
                    k2 = 0;
                } // X Y Z order
                else if (x0 >= z0) {
                    i1 = 1;
                    j1 = 0;
                    k1 = 0;
                    i2 = 1;
                    j2 = 0;
                    k2 = 1;
                } // X Z Y order
                else {
                    i1 = 0;
                    j1 = 0;
                    k1 = 1;
                    i2 = 1;
                    j2 = 0;
                    k2 = 1;
                } // Z X Y order
            }
            else { // x0<y0
                if (y0 < z0) {
                    i1 = 0;
                    j1 = 0;
                    k1 = 1;
                    i2 = 0;
                    j2 = 1;
                    k2 = 1;
                } // Z Y X order
                else if (x0 < z0) {
                    i1 = 0;
                    j1 = 1;
                    k1 = 0;
                    i2 = 0;
                    j2 = 1;
                    k2 = 1;
                } // Y Z X order
                else {
                    i1 = 0;
                    j1 = 1;
                    k1 = 0;
                    i2 = 1;
                    j2 = 1;
                    k2 = 0;
                } // Y X Z order
            }
            // A step of (1,0,0) in (i,j,k) means a step of (1-c,-c,-c) in (x,y,z),
            // a step of (0,1,0) in (i,j,k) means a step of (-c,1-c,-c) in (x,y,z), and
            // a step of (0,0,1) in (i,j,k) means a step of (-c,-c,1-c) in (x,y,z), where
            // c = 1/6.
            const x1 = x0 - i1 + G3; // Offsets for second corner in (x,y,z) coords
            const y1 = y0 - j1 + G3;
            const z1 = z0 - k1 + G3;
            const x2 = x0 - i2 + 2.0 * G3; // Offsets for third corner in (x,y,z) coords
            const y2 = y0 - j2 + 2.0 * G3;
            const z2 = z0 - k2 + 2.0 * G3;
            const x3 = x0 - 1.0 + 3.0 * G3; // Offsets for last corner in (x,y,z) coords
            const y3 = y0 - 1.0 + 3.0 * G3;
            const z3 = z0 - 1.0 + 3.0 * G3;
            // Work out the hashed gradient indices of the four simplex corners
            const ii = i & 255;
            const jj = j & 255;
            const kk = k & 255;
            // Calculate the contribution from the four corners
            let t0 = 0.6 - x0 * x0 - y0 * y0 - z0 * z0;
            if (t0 < 0)
                n0 = 0.0;
            else {
                const gi0 = ii + perm[jj + perm[kk]];
                t0 *= t0;
                n0 = t0 * t0 * (permGrad3x[gi0] * x0 + permGrad3y[gi0] * y0 + permGrad3z[gi0] * z0);
            }
            let t1 = 0.6 - x1 * x1 - y1 * y1 - z1 * z1;
            if (t1 < 0)
                n1 = 0.0;
            else {
                const gi1 = ii + i1 + perm[jj + j1 + perm[kk + k1]];
                t1 *= t1;
                n1 = t1 * t1 * (permGrad3x[gi1] * x1 + permGrad3y[gi1] * y1 + permGrad3z[gi1] * z1);
            }
            let t2 = 0.6 - x2 * x2 - y2 * y2 - z2 * z2;
            if (t2 < 0)
                n2 = 0.0;
            else {
                const gi2 = ii + i2 + perm[jj + j2 + perm[kk + k2]];
                t2 *= t2;
                n2 = t2 * t2 * (permGrad3x[gi2] * x2 + permGrad3y[gi2] * y2 + permGrad3z[gi2] * z2);
            }
            let t3 = 0.6 - x3 * x3 - y3 * y3 - z3 * z3;
            if (t3 < 0)
                n3 = 0.0;
            else {
                const gi3 = ii + 1 + perm[jj + 1 + perm[kk + 1]];
                t3 *= t3;
                n3 = t3 * t3 * (permGrad3x[gi3] * x3 + permGrad3y[gi3] * y3 + permGrad3z[gi3] * z3);
            }
            // Add contributions from each corner to get the final noise value.
            // The result is scaled to stay just inside [-1,1]
            return 32.0 * (n0 + n1 + n2 + n3);
        };
    }
    /**
     * Creates a 4D noise function
     * @param random the random function that will be used to build the permutation table
     * @returns {NoiseFunction4D}
     */
    function createNoise4D(random = Math.random) {
        const perm = buildPermutationTable(random);
        // precalculating these leads to a ~10% speedup
        const permGrad4x = new Float64Array(perm).map(v => grad4[(v % 32) * 4]);
        const permGrad4y = new Float64Array(perm).map(v => grad4[(v % 32) * 4 + 1]);
        const permGrad4z = new Float64Array(perm).map(v => grad4[(v % 32) * 4 + 2]);
        const permGrad4w = new Float64Array(perm).map(v => grad4[(v % 32) * 4 + 3]);
        return function noise4D(x, y, z, w) {
            let n0, n1, n2, n3, n4; // Noise contributions from the five corners
            // Skew the (x,y,z,w) space to determine which cell of 24 simplices we're in
            const s = (x + y + z + w) * F4; // Factor for 4D skewing
            const i = fastFloor(x + s);
            const j = fastFloor(y + s);
            const k = fastFloor(z + s);
            const l = fastFloor(w + s);
            const t = (i + j + k + l) * G4; // Factor for 4D unskewing
            const X0 = i - t; // Unskew the cell origin back to (x,y,z,w) space
            const Y0 = j - t;
            const Z0 = k - t;
            const W0 = l - t;
            const x0 = x - X0; // The x,y,z,w distances from the cell origin
            const y0 = y - Y0;
            const z0 = z - Z0;
            const w0 = w - W0;
            // For the 4D case, the simplex is a 4D shape I won't even try to describe.
            // To find out which of the 24 possible simplices we're in, we need to
            // determine the magnitude ordering of x0, y0, z0 and w0.
            // Six pair-wise comparisons are performed between each possible pair
            // of the four coordinates, and the results are used to rank the numbers.
            let rankx = 0;
            let ranky = 0;
            let rankz = 0;
            let rankw = 0;
            if (x0 > y0)
                rankx++;
            else
                ranky++;
            if (x0 > z0)
                rankx++;
            else
                rankz++;
            if (x0 > w0)
                rankx++;
            else
                rankw++;
            if (y0 > z0)
                ranky++;
            else
                rankz++;
            if (y0 > w0)
                ranky++;
            else
                rankw++;
            if (z0 > w0)
                rankz++;
            else
                rankw++;
            // simplex[c] is a 4-vector with the numbers 0, 1, 2 and 3 in some order.
            // Many values of c will never occur, since e.g. x>y>z>w makes x<z, y<w and x<w
            // impossible. Only the 24 indices which have non-zero entries make any sense.
            // We use a thresholding to set the coordinates in turn from the largest magnitude.
            // Rank 3 denotes the largest coordinate.
            // Rank 2 denotes the second largest coordinate.
            // Rank 1 denotes the second smallest coordinate.
            // The integer offsets for the second simplex corner
            const i1 = rankx >= 3 ? 1 : 0;
            const j1 = ranky >= 3 ? 1 : 0;
            const k1 = rankz >= 3 ? 1 : 0;
            const l1 = rankw >= 3 ? 1 : 0;
            // The integer offsets for the third simplex corner
            const i2 = rankx >= 2 ? 1 : 0;
            const j2 = ranky >= 2 ? 1 : 0;
            const k2 = rankz >= 2 ? 1 : 0;
            const l2 = rankw >= 2 ? 1 : 0;
            // The integer offsets for the fourth simplex corner
            const i3 = rankx >= 1 ? 1 : 0;
            const j3 = ranky >= 1 ? 1 : 0;
            const k3 = rankz >= 1 ? 1 : 0;
            const l3 = rankw >= 1 ? 1 : 0;
            // The fifth corner has all coordinate offsets = 1, so no need to compute that.
            const x1 = x0 - i1 + G4; // Offsets for second corner in (x,y,z,w) coords
            const y1 = y0 - j1 + G4;
            const z1 = z0 - k1 + G4;
            const w1 = w0 - l1 + G4;
            const x2 = x0 - i2 + 2.0 * G4; // Offsets for third corner in (x,y,z,w) coords
            const y2 = y0 - j2 + 2.0 * G4;
            const z2 = z0 - k2 + 2.0 * G4;
            const w2 = w0 - l2 + 2.0 * G4;
            const x3 = x0 - i3 + 3.0 * G4; // Offsets for fourth corner in (x,y,z,w) coords
            const y3 = y0 - j3 + 3.0 * G4;
            const z3 = z0 - k3 + 3.0 * G4;
            const w3 = w0 - l3 + 3.0 * G4;
            const x4 = x0 - 1.0 + 4.0 * G4; // Offsets for last corner in (x,y,z,w) coords
            const y4 = y0 - 1.0 + 4.0 * G4;
            const z4 = z0 - 1.0 + 4.0 * G4;
            const w4 = w0 - 1.0 + 4.0 * G4;
            // Work out the hashed gradient indices of the five simplex corners
            const ii = i & 255;
            const jj = j & 255;
            const kk = k & 255;
            const ll = l & 255;
            // Calculate the contribution from the five corners
            let t0 = 0.6 - x0 * x0 - y0 * y0 - z0 * z0 - w0 * w0;
            if (t0 < 0)
                n0 = 0.0;
            else {
                const gi0 = ii + perm[jj + perm[kk + perm[ll]]];
                t0 *= t0;
                n0 = t0 * t0 * (permGrad4x[gi0] * x0 + permGrad4y[gi0] * y0 + permGrad4z[gi0] * z0 + permGrad4w[gi0] * w0);
            }
            let t1 = 0.6 - x1 * x1 - y1 * y1 - z1 * z1 - w1 * w1;
            if (t1 < 0)
                n1 = 0.0;
            else {
                const gi1 = ii + i1 + perm[jj + j1 + perm[kk + k1 + perm[ll + l1]]];
                t1 *= t1;
                n1 = t1 * t1 * (permGrad4x[gi1] * x1 + permGrad4y[gi1] * y1 + permGrad4z[gi1] * z1 + permGrad4w[gi1] * w1);
            }
            let t2 = 0.6 - x2 * x2 - y2 * y2 - z2 * z2 - w2 * w2;
            if (t2 < 0)
                n2 = 0.0;
            else {
                const gi2 = ii + i2 + perm[jj + j2 + perm[kk + k2 + perm[ll + l2]]];
                t2 *= t2;
                n2 = t2 * t2 * (permGrad4x[gi2] * x2 + permGrad4y[gi2] * y2 + permGrad4z[gi2] * z2 + permGrad4w[gi2] * w2);
            }
            let t3 = 0.6 - x3 * x3 - y3 * y3 - z3 * z3 - w3 * w3;
            if (t3 < 0)
                n3 = 0.0;
            else {
                const gi3 = ii + i3 + perm[jj + j3 + perm[kk + k3 + perm[ll + l3]]];
                t3 *= t3;
                n3 = t3 * t3 * (permGrad4x[gi3] * x3 + permGrad4y[gi3] * y3 + permGrad4z[gi3] * z3 + permGrad4w[gi3] * w3);
            }
            let t4 = 0.6 - x4 * x4 - y4 * y4 - z4 * z4 - w4 * w4;
            if (t4 < 0)
                n4 = 0.0;
            else {
                const gi4 = ii + 1 + perm[jj + 1 + perm[kk + 1 + perm[ll + 1]]];
                t4 *= t4;
                n4 = t4 * t4 * (permGrad4x[gi4] * x4 + permGrad4y[gi4] * y4 + permGrad4z[gi4] * z4 + permGrad4w[gi4] * w4);
            }
            // Sum up and scale the result to cover the range [-1,1]
            return 27.0 * (n0 + n1 + n2 + n3 + n4);
        };
    }
    /**
     * Builds a random permutation table.
     * This is exported only for (internal) testing purposes.
     * Do not rely on this export.
     * @private
     */
    function buildPermutationTable(random) {
        const tableSize = 512;
        const p = new Uint8Array(tableSize);
        for (let i = 0; i < tableSize / 2; i++) {
            p[i] = i;
        }
        for (let i = 0; i < tableSize / 2 - 1; i++) {
            const r = i + ~~(random() * (256 - i));
            const aux = p[i];
            p[i] = p[r];
            p[r] = aux;
        }
        for (let i = 256; i < tableSize; i++) {
            p[i] = p[i - 256];
        }
        return p;
    }
    //# sourceMappingURL=simplex-noise.js.map
    ;// ../src/App.ts
    //
    voxels.setVoxelId(128, 1, 128, 0);
    voxels.setVoxelId(128, 2, 128, 0);
    //
    // world.onPlayerJoin(({entity}) => {
    // 	new Player(entity)
    // })

    (async () => {
        const n = 256;
        const r = 100 ** 2;
        const noise = createNoise2D();
        for (let x = 0; x < 256; x++) {
            for (let z = 0; z < 256; z++) {
                const ym = heights(x, z);
                for (let y = 0; y < ym; y++) {
                    voxels.setVoxel(x, y, z, 'dirt');
                }
                voxels.setVoxel(x, ym, z, 'grass');
            }
            await sleep(100);
        }
        function heights(x, z) {
            const noiseScale = 1 / 128;
            const center = 128;
            // 辐射渐变计算（平原半径扩大15%）
            const dx = (x - center) / (center);
            const dz = (z - center) / (center);
            const distance = Math.sqrt(dx * dx + dz * dz) * 0.9; // 压缩距离增强连续性
            // 三级噪声混合系统
            const plainNoise = (noise(x * noiseScale * 2, z * noiseScale * 2) + 1) * 0.5; // ±0.5米波动
            // 山脉连片生成（三层噪声混合）
            const mountainBase = Math.pow((noise(x * noiseScale * 0.7, z * noiseScale * 0.7) + 1) / 2, 2); // 基础形状
            const mountainDetail = (noise(x * noiseScale * 3, z * noiseScale * 3) + 1) / 4; // 表面细节
            const mountainRidge = Math.abs(noise(x * noiseScale * 0.3, z * noiseScale * 0.3)); // 山脉走向
            // 最终山体高度（确保最小高度差）
            const mountainHeight = (mountainBase * 0.6 + mountainDetail * 0.3 + mountainRidge * 0.1) * 120;
            // 渐进过渡系统（三阶平滑）
            const transition = smoothstep(0.6, 0.8, distance) *
                smoothstep(0.7, 0.9, distance) *
                (1 - Math.exp(-5 * distance));
            return Math.floor(
            // 盆地基底（中心42米，边缘35米）
            10 - 7 * Math.pow(distance, 0.25) +
                // 平原细节（±0.5米）
                plainNoise * (1 - transition) * 3 +
                // 山脉系统（带边缘增强）
                mountainHeight * Math.pow(transition, 1.5) * 1.2);
        }
        function smoothstep(min, max, value) {
            const t = Math.max(0, Math.min(1, (value - min) / (max - min)));
            return t * t * (3 - 2 * t);
        }
    })();

    ;
};
d();